Industrial IoT Transforms Field Service Management

Summary

Reactive field service often involves unacceptably long downtime – particularly for critical equipment. To mitigate this risk, users have internal maintenance staffs and manage extensive spare parts inventories. Now, IoT-enabled remote monitoring, analytics, and proactive maintenance offers opportunities for service providers to reduce or nearly eliminate unplanned downtime at their clients' facilities.

This opportunity requires a solution that integrates disparate systems and associated business processes for remote monitoring, predictive analytics, and field service management (FSM). This "FSM 2.0" approach can enable operating improvements that provide industrial organizations with a competitive advantage to help boost shareholder value.

The Ugly Side of Reactive Field Service

Today, most field service is reactive, with the user calling for service after the device fails. For a mission-critical piece of equipment that impacts the manufacturer's ability to fill customer orders, a failure can rapidly gain intense management attention.

Service Response

The approach used to schedule the field service technician usually optimizes internal costs without enough consideration of the impact on the user's needs. In addition, field service usually requires two visits – one to inspect and diagnose the problem to identify the needed parts and skills, and a second visit to implement the repair. This can result in extensive downtime and lost production, with unacceptable impact on the user's business.

Customer Pain

To mitigate the negative business impact of extended downtime, many manufacturing companies have an onsite, general-purpose maintenance staff with a large inventory of replacement parts. When a failure occurs, the intensive management-level attention often motivates those maintenance technicians to make shortsighted decisions that can lead to faster, but not necessary complete repairs. Without appropriate follow up, problems are likely to continue, resulting in reduced mean time between failures (MTBF) and longer mean time to repair (MTTR).

The trend toward shorter MTBF and longer MTTR will become a greater problem as equipment becomes increasingly complex with mechatronics, more sophisticated software, and advanced intellectual property. This, in turn, will make it increasingly impractical for an onsite craftsperson without deep training and experience with the particularly technology to affect optimal repairs.

Prevent Unplanned Production Interruptions

To avoid equipment failures, a preventive maintenance (PM) strategy is often deployed. PM assumes that wear from usage leads to failure, and the failure interval – MTBF – can be predicted. The PM approach schedules maintenance in a shorter interval than the expected failures. But, ARC Advisory Group research indicates that a failure pattern based on usage applies to just 18 percent of assets. The other 82 percent have random failures, and regular preventive maintenance may cause more problems (due to errors) then prevent. The alternative is a proactive approach using predictive maintenance (PdM) for industrial assets. This involves condition monitoring and predictive analytics with alerts containing diagnostic information for problem identification and resolution.

Industrial IoT-Enabled Proactive Field Service

Implementing an Industrial IoT strategy for proactive field service involves intelligence at the equipment and a cloud application for analytics, alerts, and scheduling. The analytics can be segmented into engineered algorithms and machine learning. Specific classes of equipment (like large power transmission transformers) have well-researched and understood failure patterns that have been used to create algorithms to predict failures. Advanced pattern-recognition and other types of machine learning provide a good fit with more distinct or unique equipment or processes. In both cases, the alert needs to contain information about the cause so that it is credible to the technician, who will then diagnose and repair the problem.

Engage with the Needed Skills and Parts

Of course, to successfully avoid costly unplanned downtime, the resources – skills, tools, and parts – must be scheduled and a repair executed before the failure occurs. With the advanced notice of impending failures made possible with IoT and analytics, field service managers can send the appropriate talent for a particular job to the customer site, equipped with the correct tools and spares, to make the correct repairs prior to failure, thus avoiding unplanned downtime. (To meet the service level agreement, it is not unknown for suppliers to send anyone who might be available to a customer site, including an administrative person.)

Often, breakdowns can be resolved online via software updates or configuration changes performed remotely via the internet. Also, minor tasks like changing a filter or making an adjustment can sometimes be performed by remotely directing local resources like the operator, a craftsperson, or a general-purpose technician.

Dramatically Decreasing Unscheduled Downtime

The potential of approaching zero unscheduled downtime using IoT-enabled predictive maintenance can be truly transformative for a manufacturing business. For operations and production, this enables improvements in material and labor losses, inventory (less buffer stock), capacity, on-time shipments, customer satisfaction, revenue growth, warranty costs, and much more for a competitive advantage with higher shareholder value.

Early Detection

The current run-to-failure approach allows a problem with a small component to cascade into more extensive equipment damage – much like not changing your car's engine oil can lead to a seized engine and a $5,000 repair bill. Remote monitoring allows problems to be identified and repairs made without causing a major disruption due to the associated unplanned downtime.

Improved FSM Business Processes

Obviously, going from a "two-pass" service delivery to one provides a huge improvement in MTTR along with significantly lower costs. Remote, IoT-enabled condition monitoring and analytics provide much of the information normally obtained in the first pass inspection. Advance notice to plan and execute repairs also provides the potential to significantly decrease unplanned downtime. Today's Industrial Internet of Things-enabled remote monitoring and analytics provide opportunities for industrial organizations to reevaluate their strategy for executing maintenance. Outsourcing maintenance to equipment suppliers or third-party service providers that employ a "FSM 2.0" approach not only becomes practical, but may also become necessary as equipment becomes increasingly technically sophisticated. In certain industries, the equipment OEM's are already commonly tasked with performing maintenance and repairs for their equipment and systems.

Conclusion

FSM 2.0 offers opportunities for business process transformation that benefits end users, service providers, and OEMs.

• Industrial end users should consider the availability of FSM 2.0 capabilities with IoT-enabled predictive maintenance when choosing an OEM or service provider
• OEMs should re-evaluate their own field service programs to identify potential opportunities for revenue growth with aftermarket services based on FSM 2.0.  

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Keywords: Field Service Management, Industrial IoT, MTTR, MTBF, ARC Advisory Group.